The mammalian SWI/SNF (mSWI/SNF) multi-protein complexes regulate chromatin structure through ATP-dependent nucleosome remodeling and thereby control many key cellular processes (Wilson, B. G. and C. W. Roberts (2011). Nat Rev Cancer 11(7): 481-492). Several subunits of the mSWI/SNF complexes have roles as tumor suppressors, and recent genomic studies revealed recurrent mutations in several of these subunits, with a collective mutation frequency of approximately 20% across all cancers (Kadoch, C., Hargreaves, D. C., et al. (2013) Nat Genet. 45: 592-601). The catalytic SWI/SNF subunit BRG1, also known as SMARCA4, is frequently mutated in lung adenocarcinomas and other cancer types (Becker, T. M., S. Haferkamp, et al. (2009) Mol Cancer 8: 4.)(Imielinski, M., A. H. Berger, et al. (2012) Cell 150(6): 1107-1120).
The mechanisms by which mSWI/SNF mutations contribute to tumorigenesis remain poorly understood, and their inactivation presents a challenge for devising therapeutic strategies against these genetic lesions. Mutations in specific subunits of mSWI/SNF complexes are found in distinct cancer types. Overall, mSWI/SNF complexes have emerged as the most frequently mutated class of chromatin regulators in cancer; at least six subunits of the complex have been found to be specifically inactivated at high frequencies in cancers, including subsets of ovary, breast, kidney, lung, pancreas, uterus, bladder, stomach, colon, and liver (Kadoch, C., Hargreaves, D. C., et al. (2013) Nat Genet. 45: 592-601).
BRM (also known as SMARCA2) is the paralog of BRG1 (or BRM/SWI2-related gene 1, also known as SMARCA4), and these two proteins function as mutually exclusive ATP-dependent subunits within the mammalian SWI/SNF chromatin remodeling complex. Either BRM or BRG1 is required for cells to assemble a catalytically active SWI/SNF complex. Multiple variants of the SWI/SNF complex have been characterized with differing subunit composition, but only one catalytic subunit (BRM or BRG1) is present in each complex.
BRG1 has been shown to function as a tumor suppressor and is significantly mutated in human cancers (Medina, Romero et al. 2008; Becker, Haferkamp et al. 2009). Evidence for the tumor suppressive function of BRG1 has been demonstrated by re-expression of wild type BRG1 in BRG1-mutant cell lines, resulting in differentiation and cell cycle arrest (Hendricks, K. B., F. Shanahan, et al. (2004) Mol Cell Biol 24(1): 362-376, Dunaief, J. L., B. E. Strober, et al. (1994) Cell 79(1): 119-130). Brg1+/− mice develop mammary carcinoma with a 10% incidence in one year (Bultman, S. J., J. I. Herschkowitz, et al (2008) Oncogene 27(4): 460-468). Loss-of-function mutations in BRG1 have been identified in ˜30% of established non-small-cell lung cancer lines, and silencing of BRG1 is found in many other cancer cell lines and tumor samples, including lung, pancreatic, and ovarian cancers, melanomas, and pediatric rhabdoid sarcomas (Wilson et al.; Roberts et al.). Importantly, recent results from the Cancer Genome Atlas (TCGA) project identified BRG1 mutations as one of the most prominent mutations in tumor samples from patients with lung adenocarcinoma, occurring in ˜10% of all tumor samples (a rate similar to other well characterized oncogenes and tumor suppressors such as EGFR and LKB1)(Imielinski et al. (2012) Cell 150(6): 1107-1120). Therefore, identifying the key synthetic lethal nodes in mSWI/SNF mutant cancers, such as in BRG1-mutant/deficient cancers will be critical towards developing the appropriate therapeutic strategies for targeting such cancers.
There is an increasing body of evidence that suggests a patient's genetic profile can be determinative to a patient's responsiveness to a therapeutic treatment. Given the numerous therapies available to an individual having cancer, a determination of the genetic factors that influence, for example, response to a particular drug, could be used to provide a patient with a personalized treatment regime. Such personalized treatment regimens offer the potential to maximize therapeutic benefit to the patient while minimizing related side effects that can be associated with alternative and less effective treatment regimens. Thus, there is a need to identify factors which can be used to predict whether a patient is likely to respond to a particular therapy. It is of particular interest to determine predictive factors in the field of cancer biology, and to therapeutically exploit discoveries pertaining to key synthetic lethal nodes in the various SWI/SNF mutant cancers.